class_docstr: Cifar10 data set.
  
  Described by http://www.cs.toronto.edu/~kriz/cifar.html.
docstr: Parses a single tf.Example into image and label tensors.
docstr_tok: ["Parses","a","single","tf.Example","into","image","and","label","tensors","."]
code: def parser(self, serialized_example):
      """Parses a single tf.Example into image and label tensors."""
      # Dimensions of the images in the CIFAR-10 dataset.
      # See http://www.cs.toronto.edu/~kriz/cifar.html for a description of the
      # input format.
      features = tf.parse_single_example(
          serialized_example,
          features={
              "image": tf.FixedLenFeature([], tf.string),
              "label": tf.FixedLenFeature([], tf.int64),
          },
      )
      image = tf.decode_raw(features["image"], tf.uint8)
      image.set_shape([DEPTH * HEIGHT * WIDTH])
  
      # Reshape from [depth * height * width] to [depth, height, width].
      image = tf.cast(
          tf.transpose(
              tf.reshape(image, [DEPTH, HEIGHT, WIDTH]), [1, 2, 0]
          ),
          tf.float32,
      )
      label = tf.cast(features["label"], tf.int32)
  
      # Custom preprocessing.
      image = self.preprocess(image)
  
      return image, label
  
file_path: dragonfly/examples/nas/cg/cifar/cifar10.py
imports: import os
  import tensorflow
label_desc: Use image node_id 3 for calling the Cifar10DataSet obj's underlying member method code with example usage: obj.parser(serialized_example) and returns: image,  label